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Sheng L, Yuan E, Yuan F, Song B. Amide proton transfer-weighted imaging of the abdomen: Current progress and future directions. Magn Reson Imaging 2024; 107:88-99. [PMID: 38242255 DOI: 10.1016/j.mri.2024.01.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 01/13/2024] [Accepted: 01/14/2024] [Indexed: 01/21/2024]
Abstract
The chemical exchange saturation transfer technique serves as a valuable tool for generating in vivo image contrast based on the content of various proton groups, including amide protons, amine protons, and aliphatic protons. Among these, amide proton transfer-weighted (APTw) imaging has seen extensive development as a means to assess the biochemical status of lesions. The exchange from saturated amide protons to bulk water protons during and following the saturation ratio frequency pulse contributes to detectable APT signals. While APTw imaging has garnered significant attention in the central nervous system, demonstrating noteworthy findings in cerebral neoplasia, stroke, and Alzheimer's disease over the past decade, its application in the abdomen has been a relatively recent progression. Notably, studies have explored its utility in hepatocellular carcinoma, prostate cancer, and cervical carcinoma within the abdominal context. Despite these advancements, there is a paucity of reviews on APTw imaging in abdominal applications. This paper aims to fill this gap by providing a concise overview of the fundamental theories underpinning APTw imaging. Additionally, we systematically summarize its diverse clinical applications in the abdomen, with a particular focus on the digestive and urogenital systems. Finally, the manuscript concludes by discussing technical limitations and factors influencing APTw imaging in abdominal applications, along with prospects for future research.
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Affiliation(s)
- Liuji Sheng
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Enyu Yuan
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Fang Yuan
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
| | - Bin Song
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Department of Radiology, Sanya People's Hospital, Sanya, Hainan, China.
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Wen Y, Song Z, Li Q, Zhang D, Li X, Yu J, Li Z, Ren X, Zhang J, Liu Q, Huang J, Zeng D, Tang Z. Development and validation of a model for predicting the expression of Ki-67 in pancreatic ductal adenocarcinoma with radiological features and dual-energy computed tomography quantitative parameters. Insights Imaging 2024; 15:41. [PMID: 38353857 PMCID: PMC10866831 DOI: 10.1186/s13244-024-01617-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 12/21/2023] [Indexed: 02/17/2024] Open
Abstract
OBJECTIVE To construct and validate a model based on the dual-energy computed tomography (DECT) quantitative parameters and radiological features to predict Ki-67 expression levels in pancreatic ductal adenocarcinoma (PDAC). MATERIALS AND METHODS Data from 143 PDAC patients were analysed. The variables of clinic, radiology and DECT were evaluated. In the arterial phase and portal venous phase (PVP), the normalized iodine concentration (NIC), normalized effective atomic number and slope of the spectral attenuation curves were measured. The extracellular volume fraction (ECVf) was measured in the equilibrium phase. Univariate analysis was used to screen independent risk factors to predict Ki-67 expression. The Radiology, DECT and DECT-Radiology models were constructed, and their diagnostic effectiveness and clinical applicability were obtained through area under the curve (AUC) and decision curve analysis, respectively. The nomogram was established based on the optimal model, and its goodness-of-fit was assessed by a calibration curve. RESULTS Computed tomography reported regional lymph node status, NIC of PVP, and ECVf were independent predictors for Ki-67 expression prediction. The AUCs of the Radiology, DECT, and DECT-Radiology models were 0.705, 0.884, and 0.905, respectively, in the training cohort, and 0.669, 0.835, and 0.865, respectively, in the validation cohort. The DECT-Radiology nomogram was established based on the DECT-Radiology model, which showed the highest net benefit and satisfactory consistency. CONCLUSIONS The DECT-Radiology model shows favourable predictive efficacy for Ki-67 expression, which may be of value for clinical decision-making in PDAC patients. CRITICAL RELEVANCE STATEMENT The DECT-Radiology model could contribute to the preoperative and non-invasive assessment of Ki-67 expression of PDAC, which may help clinicians to screen out PDAC patients with high Ki-67 expression. KEY POINTS • Dual-energy computed tomography (DECT) can predict Ki-67 in pancreatic ductal adenocarcinoma (PDAC). • The DECT-Radiology model facilitates preoperative and non-invasive assessment of PDAC Ki-67 expression. • The nomogram may help screen out PDAC patients with high Ki-67 expression.
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Affiliation(s)
- Youjia Wen
- Chongqing General Hospital, No.118, Xingguang Avenue, Liangjiang New Area, Chongqing, China
| | - Zuhua Song
- Chongqing General Hospital, No.118, Xingguang Avenue, Liangjiang New Area, Chongqing, China
| | - Qian Li
- Chongqing General Hospital, No.118, Xingguang Avenue, Liangjiang New Area, Chongqing, China
| | - Dan Zhang
- Chongqing General Hospital, No.118, Xingguang Avenue, Liangjiang New Area, Chongqing, China
| | - Xiaojiao Li
- Chongqing General Hospital, No.118, Xingguang Avenue, Liangjiang New Area, Chongqing, China
| | - Jiayi Yu
- Chongqing General Hospital, No.118, Xingguang Avenue, Liangjiang New Area, Chongqing, China
| | - Zongwen Li
- Chongqing General Hospital, No.118, Xingguang Avenue, Liangjiang New Area, Chongqing, China
| | - Xiaofang Ren
- Chongqing General Hospital, No.118, Xingguang Avenue, Liangjiang New Area, Chongqing, China
| | - Jiayan Zhang
- Chongqing General Hospital, No.118, Xingguang Avenue, Liangjiang New Area, Chongqing, China
| | - Qian Liu
- Chongqing General Hospital, No.118, Xingguang Avenue, Liangjiang New Area, Chongqing, China
| | - Jie Huang
- Chongqing General Hospital, No.118, Xingguang Avenue, Liangjiang New Area, Chongqing, China
| | - Dan Zeng
- Chongqing General Hospital, No.118, Xingguang Avenue, Liangjiang New Area, Chongqing, China
| | - Zhuoyue Tang
- Chongqing General Hospital, No.118, Xingguang Avenue, Liangjiang New Area, Chongqing, China.
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